
TRAIL is a member of the tumor necrosis factor family implicated in programmed cell death. We recently demonstrated that TRAIL can serve as a useful biomarker for distinguishing between bacterial and viral infections when computationally combined with CRP and IP-10 (Oved et al. 2015). Here we report that low TRAIL concentration in the blood is significantly correlated with poor patient prognosis and higher disease severity.
Methods:
We studied 765 hospitalized and emergency department patients with acute infection and controls with no apparent infection, prospectively recruited between 2009 and 2013. Patient etiology (319 bacterial, 334 viral, and 112 control) was determined by a panel of three independent experts based on comprehensive clinical and laboratory assessment that included two multiplex-PCR panels applied to nasal swabs (Seeplex-RV15/PB6). Serum TRAIL levels were measured using commercially available ELISA kits (MeMed, IL).
Results:
TRAIL serum levels were significantly decreased in bacterial patients and increased in viral patients as compared to controls (average±SD [pg/ml]: bacterial 45±33; viral 145±110; controls 77±32, P<10-15). Further analysis of the infectious patients group (n=653), revealed that patients with TRAIL levels lower than 25 pg/ml (n=93), were characterized by more severe disease outcome compared to patients with higher TRAIL levels (n=560) including longer hospitalization duration (7.5±11.3 vs 1.9±2.2 days, P<10-5), and need for mechanical ventilation and ICU admission (6/93 vs 0/560, P<10-5). Severe clinical syndromes such as bacteremia and septic shock were also statistically enriched in the low TRAIL sub-group (64% (7/11) of all bacteremia cases P<10-3, and 100% (7/7) of all septic shock cases, P<10-6).
Conclusion:
TRAIL serum levels lower than 25 pg/ml were correlated with longer hospitalization duration, ICU admission and severe clinical syndromes. These results suggest that TRAIL has the potential to serve as a marker for disease severity. Timely measurement of TRAIL serum levels might therefore enable a more accurate risk stratification, treatment optimization, and potentially better patient outcome.

K. Oved,
MeMed Diagnostics:
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E. Eden, MeMed Diagnostics: Board Member , Employee and Shareholder , Salary